This disclosure relates to energy management, and more particularly to electrical device control methods and electrical energy consumption systems. The disclosure finds particular application to energy management of energy consuming devices, or appliances, for example, dishwashers, clothes washers, dryers, HVAC systems, etc.
In order to reduce high peak power demand, many utilities have instituted time of use (TOU) metering and rates, which include higher rates for energy usage during on-peak times and lower rates for energy usage during off-peak times. Other dynamic rate scenarios include critical peak pricing, day ahead hourly rates and even real time rates based on wholesale electric rates charged by the Utilities, Regional Transmission Organizations (RTO)/Independent System Operators (ISO). As a result, consumers are provided with an incentive to use electricity at off-peak times rather than on-peak times and to reduce overall energy consumption of appliances at all times. In addition, Utilities, Regional Transmission Organizations (RTO)/Independent System Operators (ISO) and third party aggregators may be willing to provide payments to consumers for short term reductions in load to provide “ancillary services,” such as providing additional spinning reserves capacity or frequency regulation.
Utility power systems become “smart” and demand response enabled by employing a head end management system, such as a company or program responsible for monitoring and running a demand response program. This usually requires equipment and time investments by utilities to install automatic meter reading (AMR) systems, advanced metering infrastructure, or other types of “smart” utility meters in each home. AMR systems, for example, provide for automatically collecting and holding consumption, diagnostic, and status data from water meter or energy metering devices (e.g., for water, gas, or electricity) and transferring that data wirelessly to a meter reader when queried by the meter reader. Advanced metering infrastructure (AMI) represents the application of networking technology to read and manage meter systems that go beyond AMR. These AMI systems enable remote and automatic reading of the meter data and transmitting it back to a central database for billing, troubleshooting, and analysis. In addition the AMI system can remotely disconnect meters as well as report outages when meters are no longer responding due to a localized power failure. The meters in an AMI system are often referred to as “smart meters,” since they can use and analyze the collected meter data based on programmed logic.
Smart grid applications improve the ability of electricity producers and consumers to communicate with one another and make decisions about how and when to produce and consume power. Demand response (DR) technology, for example, allows customers to shift from an event based demand response where the utility requests the shedding of load, towards a more 24/7 based demand response where the customer sees incentives for controlling load all the time, such as in providing “Ancillary Services.” One advantage of a smart grid application is time-based pricing. Customers who traditionally pay a fixed rate for kWh and kW/month can set their threshold and adjust their usage to take advantage of fluctuating prices. Another advantage, is being able to closely monitor, shift, and balance load in a way that allows the customer to save peak load and not only save on kWh and kW/month, but also be able to trade what they have saved in an energy market. Similarly the smart grid will allow customers to be paid for supplying Ancillary Services—short term reductions in load to provide grid stability due to fluctuating generation sources (such as solar and wind capacity) as well as normal grid stability needs. However, this involves sophisticated energy management systems, incentives, and a viable trading market.
When TOU or DR events are ended, it is possible that a number of users turning appliances on at the same time can create an initial influx of power that is up to several times the normal load on a power grid. This initial influx could compromise a power grid as well as cause it to be fully loaded, and thus, cause a reduction or shut off in power temporarily (e.g., brown outs or black outs). In addition, expenditures to run outside “peak” plants are costly and may not be as environmentally friendly.
Therefore, there is a need to provide an improved system that can enable control when power consuming devices are started after and/or before a DR event or TOU event, and thus, provide incentive for discretional power use to be moved into the off-peak timeframe so consumers can balance their level of comfort with a desired savings amount.